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Understanding controls on primary productivity is essential for describing ecosystems and their responses to environmental change. Lake primary production is strongly controlled by inputs of nutrients and colored dissolved organic matter. While past studies have developed mathematical models of this nutrient-color paradigm, broad empirical tests of these models are scarce. We compiled data from 58 diverse and globally distributed and mostly temperate lakes to test such a model and improve understanding and prediction of the controls on lake primary production. These lakes varied widely in size (0.02-2300 km2), pelagic gross primary production (20-8000 mg C m-2 d-1), and other characteristics. The data package includes high-frequency dissolved oxygen, water temperature, wind speed, and solar radiation data as well as daily estimates of GPP and ER derived from those data. In addition, the data package includes median in-lake and stream concentrations of dissolved organic carbon and total phosphorus for a subset of 18 of those lakes. 

Rapid changes in climate and land use are having substantial and interacting impacts on lake water quality around the world. Here, we synthesized time-series data for dissolved oxygen, temperature, chlorophyll-a, total phosphorus, total nitrogen, and dissolved organic carbon at multiple depths in 822 lakes to facilitate analyses of these changes. The dataset extends from 1921–2022, with a median data duration of 29 years (range 5-102) and a median of 5 unique sampling dates per year at each lake. Lakes in the dataset have a median depth of 12.5 m (range 1.5–480 m), median surface area of 85.4 ha (range: 0.5–237000 ha) and median elevation of 264 m (range: -215–2804). The lakes are located in 18 countries across 5 continents, with latitudes ranging from -42.6 to 68.3. To facilitate interoperability with other large-scale datasets, each lake is linked to a unique hydroLAKES lake ID when possible (n = 683). 

Abstract Understanding controls on primary productivity is essential for describing ecosystems and their responses to environmental change. In lakes, pelagic gross primary productivity (GPP) is strongly controlled by inputs of nutrients and dissolved organic matter. Although past studies have developed process models of this nutrient‐color paradigm (NCP), broad empirical tests of these models are scarce. We used data from 58 globally distributed, mostly temperate lakes to test such a model and improve understanding and prediction of the controls on lake primary production. The model includes three state variables–dissolved phosphorus, terrestrial dissolved organic carbon (DOC), and phytoplankton biomass–and generates realistic predictions for equilibrium rates of pelagic GPP. We calibrated our model using a Bayesian data assimilation technique on a subset of lakes where DOC and total phosphorus (TP) loads were known. We then asked how well the calibrated model performed with a larger set of lakes. Revised parameter estimates from the updated model aligned well with existing literature values. Observed GPP varied nonlinearly with both inflow DOC and TP concentrations in a manner consistent with increasing light limitation as DOC inputs increased and decreasing nutrient limitation as TP inputs increased. Furthermore, across these diverse lake ecosystems, model predictions of GPP were highly correlated with observed values derived from high‐frequency sensor data. The GPP predictions using the updated parameters improved upon previous estimates, expanding the utility of a process model with simplified assumptions for water column mixing. Our analysis provides a model structure that may be broadly useful for understanding current and future patterns in lake primary production. 

Abstract Lake surfaces are warming worldwide, raising concerns about lake organism responses to thermal habitat changes. Species may cope with temperature increases by shifting their seasonality or their depth to track suitable thermal habitats, but these responses may be constrained by ecological interactions, life histories or limiting resources. Here we use 32 million temperature measurements from 139 lakes to quantify thermal habitat change (percentage of non-overlap) and assess how this change is exacerbated by potential habitat constraints. Long-term temperature change resulted in an average 6.2% non-overlap between thermal habitats in baseline (1978–1995) and recent (1996–2013) time periods, with non-overlap increasing to 19.4% on average when habitats were restricted by season and depth. Tropical lakes exhibited substantially higher thermal non-overlap compared with lakes at other latitudes. Lakes with high thermal habitat change coincided with those having numerous endemic species, suggesting that conservation actions should consider thermal habitat change to preserve lake biodiversity. 

Abstract Declining oxygen concentrations in the deep waters of lakes worldwide pose a pressing environmental and societal challenge. Existing theory suggests that low deep‐water dissolved oxygen (DO) concentrations could trigger a positive feedback through which anoxia (i.e., very low DO) during a given summer begets increasingly severe occurrences of anoxia in following summers. Specifically, anoxic conditions can promote nutrient release from sediments, thereby stimulating phytoplankton growth, and subsequent phytoplankton decomposition can fuel heterotrophic respiration, resulting in increased spatial extent and duration of anoxia. However, while the individual relationships in this feedback are well established, to our knowledge, there has not been a systematic analysis within or across lakes that simultaneously demonstrates all of the mechanisms necessary to produce a positive feedback that reinforces anoxia. Here, we compiled data from 656 widespread temperate lakes and reservoirs to analyze the proposed anoxia begets anoxia feedback. Lakes in the dataset span a broad range of surface area (1–126,909 ha), maximum depth (6–370 m), and morphometry, with a median time‐series duration of 30 years at each lake. Using linear mixed models, we found support for each of the positive feedback relationships between anoxia, phosphorus concentrations, chlorophyllaconcentrations, and oxygen demand across the 656‐lake dataset. Likewise, we found further support for these relationships by analyzing time‐series data from individual lakes. Our results indicate that the strength of these feedback relationships may vary with lake‐specific characteristics: For example, we found that surface phosphorus concentrations were more positively associated with chlorophyllain high‐phosphorus lakes, and oxygen demand had a stronger influence on the extent of anoxia in deep lakes. Taken together, these results support the existence of a positive feedback that could magnify the effects of climate change and other anthropogenic pressures driving the development of anoxia in lakes around the world. 

Abstract. Empirical evidence demonstrates that lakes and reservoirs are warming acrossthe globe. Consequently, there is an increased need to project futurechanges in lake thermal structure and resulting changes in lakebiogeochemistry in order to plan for the likely impacts. Previous studies ofthe impacts of climate change on lakes have often relied on a single modelforced with limited scenario-driven projections of future climate for arelatively small number of lakes. As a result, our understanding of theeffects of climate change on lakes is fragmentary, based on scatteredstudies using different data sources and modelling protocols, and mainlyfocused on individual lakes or lake regions. This has precludedidentification of the main impacts of climate change on lakes at global andregional scales and has likely contributed to the lack of lake water qualityconsiderations in policy-relevant documents, such as the Assessment Reportsof the Intergovernmental Panel on Climate Change (IPCC). Here, we describe asimulation protocol developed by the Lake Sector of the Inter-SectoralImpact Model Intercomparison Project (ISIMIP) for simulating climate changeimpacts on lakes using an ensemble of lake models and climate changescenarios for ISIMIP phases 2 and 3. The protocol prescribes lakesimulations driven by climate forcing from gridded observations anddifferent Earth system models under various representative greenhouse gasconcentration pathways (RCPs), all consistently bias-corrected on a0.5∘ × 0.5∘ global grid. In ISIMIP phase 2, 11 lakemodels were forced with these data to project the thermal structure of 62well-studied lakes where data were available for calibration underhistorical conditions, and using uncalibrated models for 17 500 lakesdefined for all global grid cells containing lakes. In ISIMIP phase 3, thisapproach was expanded to consider more lakes, more models, and moreprocesses. The ISIMIP Lake Sector is the largest international effort toproject future water temperature, thermal structure, and ice phenology oflakes at local and global scales and paves the way for future simulations ofthe impacts of climate change on water quality and biogeochemistry in lakes. 

Noetzli, J., Christiansen, H.H, Guglielmin, M., Hrbáček, F., Hu, G., Isaksen, K., Magnin, F., Pogliotti, P., Smith, S. L., Zhao, L. and Streletskiy, D. A. 2024. Permafrost temperature and active layer thickness. In: State of the Climate in 2023. Bulletin of the American Meteorological Society, 105 (8), S43–S44, https://doi.org/10.1175/BAMS-D-24-0116.1